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  2. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    The storage and computation overhead is such that the standard simplex method is a prohibitively expensive approach to solving large linear programming problems. In each simplex iteration, the only data required are the first row of the tableau, the (pivotal) column of the tableau corresponding to the entering variable and the right-hand-side.

  3. George Dantzig - Wikipedia

    en.wikipedia.org/wiki/George_Dantzig

    Dantzig is known for his development of the simplex algorithm, [1] an algorithm for solving linear programming problems, and for his other work with linear programming. In statistics , Dantzig solved two open problems in statistical theory , which he had mistaken for homework after arriving late to a lecture by Jerzy Spława-Neyman .

  4. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint propagation methods are also used in conjunction with search to make a given problem simpler to solve. Other considered kinds of constraints are on real or rational numbers; solving problems on these constraints is done via variable elimination or the simplex algorithm.

  5. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    The problem of solving a system of linear inequalities dates back at least as far as Fourier, who in 1827 published a method for solving ... his simplex method, ...

  6. Revised simplex method - Wikipedia

    en.wikipedia.org/wiki/Revised_simplex_method

    The revised simplex method is mathematically equivalent to the standard simplex method but differs in implementation. Instead of maintaining a tableau which explicitly represents the constraints adjusted to a set of basic variables, it maintains a representation of a basis of the matrix representing the constraints.

  7. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    HiGHS has implementations of the primal and dual revised simplex method for solving LP problems, based on techniques described by Hall and McKinnon (2005), [6] and Huangfu and Hall (2015, 2018). [ 7 ] [ 8 ] These include the exploitation of hyper-sparsity when solving linear systems in the simplex implementations and, for the dual simplex ...

  8. Bland's rule - Wikipedia

    en.wikipedia.org/wiki/Bland's_rule

    In mathematical optimization, Bland's rule (also known as Bland's algorithm, Bland's anti-cycling rule or Bland's pivot rule) is an algorithmic refinement of the simplex method for linear optimization. With Bland's rule, the simplex algorithm solves feasible linear optimization problems without cycling. [1] [2] [3]

  9. Least absolute deviations - Wikipedia

    en.wikipedia.org/wiki/Least_absolute_deviations

    A Simplex method is a method for solving a problem in linear programming. The most popular algorithm is the Barrodale-Roberts modified Simplex algorithm. The algorithms for IRLS, Wesolowsky's Method, and Li's Method can be found in Appendix A of [7] among other methods. Checking all combinations of lines traversing any two (x,y) data points is ...